[R] R vs SPSS contrasts

[Gabor Grothendieck]

Looks like the contrast matrix for indicator is contr.SAS(n),
for deviation is contr.sum(n) and for simple is:

(diag(n) - 1/n)[, -1]

That works at least for the n = 3 example in the link.
Perhaps the others could be checked against SPSS
for a variety of values of n to be sure.

On Sun, Oct 12, 2008 at 12:32 PM, Chuck Cleland <ccleland at optonline.net> wrote:
> On 10/11/2008 3:31 PM, Ted Harding wrote:
>> Hi Folks,
>>
>> I'm comparing some output from R with output from SPSS.
>> The coefficients of the independent variables (which are
>> all factors, each at 2 levels) are identical.
>>
>> However, R's Intercept (using default contr.treatment)
>> differs from SPSS's 'constant'. It seems that the contrasts
>> were set in SPSS using
>>
>>   /CONTRAST (varname)=Simple(1)
>>
>> I can get R's Intercept to match SPSS's 'constant' if I use
>> contr.sum in R.
>>
>> Can someone please confirm that that is a correct match for
>> the SPSS "Simple(1)", with identical effect?
>>
>> And is there a convenient on-line reference where I can look
>> up what SPSS's "/CONTRAST" statements exactly mean?
>> I've done a lot of googling, withbout coming up with anything
>> satisfactory.
>>
>> With thanks,
>> Ted.
>
> Hi Ted:
>  Here are two links with the same content giving a brief description of
> SPSS simple contrasts:
>
> http://www.ats.ucla.edu/stat/spss/library/contrast.htm
> http://support.spss.com/productsext/spss/documentation/statistics/articles/contrast.htm
>
>  These pages explain how simple contrasts differ from indicator
> (contr.treatment) and deviation (contr.sum) contrasts.  For a factor
> with 3 levels, I believe you can reproduce SPSS simple contrasts (with
> the first category as reference) like this:
>
>> C(warpbreaks$tension, contr=matrix(c(-1/3,2/3,-1/3,-1/3,-1/3,2/3),
> ncol=2))
> ...
> attr(,"contrasts")
>        [,1]       [,2]
> L -0.3333333 -0.3333333
> M  0.6666667 -0.3333333
> H -0.3333333  0.6666667
> Levels: L M H
>
>  For a factor with 2 levels, like this:
>
>> C(warpbreaks$wool, contr=matrix(c(-1/2,1/2), ncol=1))
> ...
> attr(,"contrasts")
>  [,1]
> A -0.5
> B  0.5
> Levels: A B
>
>  Your description of the effect of SPSS simple contrasts - intercept
> coefficient of contr.sum and non-intercept coefficients of
> contr.treatment - sounds accurate to me.
>
> hope this helps,
>
> Chuck
>
>> --------------------------------------------------------------------
>> E-Mail: (Ted Harding) <Ted.Harding at manchester.ac.uk>
>> Fax-to-email: +44 (0)870 094 0861
>> Date: 11-Oct-08                                       Time: 20:31:53
>> ------------------------------ XFMail ------------------------------
>>
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>
> --
> Chuck Cleland, Ph.D.
> NDRI, Inc. (www.ndri.org)
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>